AI Agent Development
AI Agent Development Company
AI agents go beyond chat. They plan, call your tools and APIs, and complete multi-step work. We build agents that are scoped, observable and safe to put in front of real customers and real systems.
- Tool-calling agents connected to your APIs and data
- Human-in-the-loop approvals for risky actions
- Tracing, evals and replay for every agent run
- Single-agent and multi-agent architectures
Where it pays off.
Customer support agents
Resolve common requests end to end: look up orders, update records, issue refunds within limits, and hand over to a human with full context.
Sales and lead operations
Research accounts, enrich leads, draft outreach and update the CRM, with a rep approving what goes out.
Research and analyst agents
Gather sources, extract facts, compare options and produce cited briefs for finance, legal or market teams.
Back-office operations
Process invoices, reconcile records, triage inboxes and route approvals across your internal tools.
What we deliver.
Every engagement is fixed-scope, fixed-timeline and fully transparent.
Agent architecture
We choose the simplest design that works: a single agent with tools, a router, or coordinated specialist agents, and justify the choice.
Tools & integrations
Secure function calling into your CRM, ERP, ticketing, databases and third-party APIs, with scoped permissions.
Memory & knowledge
Short and long-term memory plus retrieval from your documents so the agent stays consistent and grounded.
Safety & oversight
Spending and action limits, approval steps, audit logs and fallbacks so an agent cannot quietly do the wrong thing.
Why teams work with us.
Handle multi-step work
Agents finish tasks that single prompts cannot, such as gathering data, deciding and then acting.
Reliability you can measure
Every agent ships with an evaluation set, so you see success rates and regressions rather than anecdotes.
Controlled autonomy
You decide what the agent can do alone and what needs a human, and can widen that over time.
Fits your existing stack
Agents plug into the systems your team already uses instead of forcing a new tool.
How we work.
1. Define the job
Write down the task, inputs, tools, success criteria and what the agent must never do.
2. Build the tools
Implement and test the actions the agent can take, with permissions and rate limits.
3. Prototype the agent
Create the first agent loop and run it against real example cases to see where it fails.
4. Evaluate & harden
Build a test set, add guardrails and approvals, and tune until quality meets the agreed bar.
5. Deploy & monitor
Ship behind a staged rollout with tracing, cost tracking and alerting.
Our stack.
Tools we use every day to ship faster and safer.
What you get.
Every engagement ships with these, minimum.
- Deployed agent with documented tools and permissions
- Evaluation suite and baseline success metrics
- Run tracing and audit logging
- Runbook for operating and extending the agent
Frequently asked questions.
What is an AI agent and how is it different from a chatbot?
A chatbot answers questions in a conversation. An AI agent can also decide on steps, call tools such as your CRM or database, and carry out a task to completion. Agents need more engineering around permissions, testing and monitoring than chatbots do.
Are AI agents reliable enough for production?
For well-scoped tasks, yes, provided they are built with evaluation, guardrails and fallbacks. We avoid open-ended autonomy and instead constrain the agent to specific tools and outcomes, with human approval for high-impact actions.
Can an agent connect to our internal systems?
Yes. We build secure tool integrations to CRMs, ERPs, ticketing systems, databases and internal APIs, using least-privilege credentials and audit logging.
What if the agent makes a mistake?
We design for it: approval steps for sensitive actions, spending and action limits, full run traces to diagnose problems, and an easy way to hand off to a person. Evaluation sets catch regressions before changes ship.
Should we use one agent or several?
Start with the simplest option. Many problems are solved by one agent with good tools. We recommend multiple specialist agents only when the task genuinely separates into distinct skills or permissions.
Ready to put an AI agent to work?
Tell us the workflow you want handled. We will scope the agent, its tools and the guardrails, and show you what a first version looks like.
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